PERBANDINGAN METODE INFERENSI FUZZY MAMDANI DAN TSUKAMOTO DALAM MELAKUKAN PREDIKSI RISIKO PENYAKIT BATU GINJAL

GUNAWAN, VERDINAN GILBERT and Rini, Dian Palupi (2025) PERBANDINGAN METODE INFERENSI FUZZY MAMDANI DAN TSUKAMOTO DALAM MELAKUKAN PREDIKSI RISIKO PENYAKIT BATU GINJAL. Undergraduate thesis, Sriwijaya University.

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Abstract

Kidney stones are one of the most common health problems and have the potential to cause chronic kidney failure if not properly addressed. To support early prevention efforts, this study aims to compare two fuzzy inference methods, namely Mamdani and Tsukamoto. The study will use 89 data points obtained from Kaggle under the title "Kidney Stones Dataset." In predicting the risk of kidney stones, this study will utilize pH, calcium, and urea as variables. The output variable represents the risk level, classified into low risk and high risk. In the prediction process, the Mamdani method will employ the Centroid method, while the Tsukamoto method will use the Weighted Average method for defuzzification. The results of the study indicate that the Mamdani method achieved prediction accuracy for 64 data, while the Tsukamoto method achieved prediction accuracy for 45 data. In terms of Mean Squared Error (MSE), the Tsukamoto method resulted in an MSE of 0.494, whereas the Mamdani method produced an MSE of 0.281. These findings demonstrate that the Mamdani inference method is more effective in predicting the risk of kidney stones.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Kidney Stones, Fuzzy Logic, Mamdani Inference, Tsukamoto Inference, Prediction, Risk
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General)
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Verdinan Gilbert Gunawan
Date Deposited:	13 Jan 2025 08:10
Last Modified:	13 Jan 2025 08:10
URI:	http://repository.unsri.ac.id/id/eprint/164400

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